Energy management of a microgrid with integration of renewable energy sources considering energy storage systems with electricity price

The growing concerns surrounding global warming, diminishing fossil fuel reserves, and the urgent need for clean energy solutions have made the electrification of transportation in microgrids (MGs) a crucial strategy for addressing these pressing challenges. Vehicle-to-grid (V2G) technology offers an efficient and cost-effective approach to integrating electric vehicles (EVs) into power grids. This research employs the unscented transform (UT) to account for uncertainties in EV charging and discharging demands, wind turbines, photovoltaic (PV) systems, load demands, and market price variations. The problem is formulated as a constrained single-objective optimization task, aimed at minimizing the total operational costs of microgrids while satisfying practical constraints. To achieve this, a novel and efficient optimization technique, the modified marine predators algorithm (MMPA), is utilized for optimizing microgrid operations. The feasibility and performance of the proposed method are validated on an IEEE test system, where simulations reveal that integrating EVs improves power dispatch among distributed generation sources, reducing both power losses and costs.